RNA methylation plays crucial roles in gene expression and has been indicated to be involved in tumorigenesis, while it is still unclear whether m1A modifications have potential roles in the prognosis of hepatocellular carcinoma (HCC). In this study, we comprehensively analyzed RNA sequencing (RNA-seq) data and clinical information using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We collected 10 m1A regulators and performed consensus clustering to determine m1A modification patterns in HCC. The CIBERSORT method was utilized to evaluate the level of immune cell infiltration. Principal component analysis was used to construct the m1A-score model. In the TCGA-LIHC cohort, the expression of all 10 m1A regulators was higher in tumor tissues than in normal control tissues, and 8 of 10 genes were closely related to the prognosis of HCC patients. Two distinct m1A methylation modification patterns (Clusters C1 and C2) were identified by the 10 regulators and were associated with different overall survival, TNM stage and tumor microenvironment (TME) characteristics. Based on the differentially expressed genes (DEGs) between C1 and C2, we identified three gene clusters (Clusters A, B and C). C1 with a better prognosis was mainly distributed in Cluster C, while Cluster A contained the fewest samples of C1. An m1A-score model was constructed using five m1A regulators related to prognosis. Patients with higher m1A scores showed a poorer prognosis than those with lower scores in the TCGA-LIHC and GSE14520 datasets. In conclusions, our study showed the vital role of m1A modification in the TME and progression of HCC. Quantitative evaluation of the m1A modification patterns of individual patients facilitates the development of more effective biomarkers for predicting the prognosis of patients with HCC.

Small nucleolar RNA host gene 14 (SNHG14) is a long non-coding RNA found to be overexpressed in various types of cancers. Moreover, the expression level of SNHG14 was closely associated with multiple clinicopathological characteristics such as prognosis, tumor differentiation, TNM stage, and lymph node metastasis. Functionally, gain- and loss-of-function of SNHG14 revealed that overexpressed SNHG14 promoted cancer cell viability, invasion, and migration, whereas its down-regulation produced the opposite effect. Mechanistically, regulating its target gene expression by sponging distinct miRNAs might be the major mechanism underlying the oncogenic functions of SNHG14. Thus, SNHG14 might be a promising prognostic biomarker and therapeutic target for cancers. In this review, we discuss the expression profile, biological function, and molecular mechanisms of SNHG14 in cancers to provide a molecular basis for the clinical utility of SNHG14 in the future.

Robust assays to quantify adeno-associated virus (AAV) vector expression and potency are essential for gene therapy development. These assays inform the efficacy, safety, and pharmacodynamic profiles of AAV development candidates. Additionally, for gene downregulation strategies such as RNAi, knockdown of endogenous genes reflects the mechanism of action of such development candidates. Therefore, a method to quantify target mRNA repression is necessary for measuring vector potency both in vitro and in vivo. Here, we report the development of a one-step reverse-transcription droplet digital PCR (RT-ddPCR) method to analyze expression of AAV vectors and the potency of AAV-RNAi vectors. This one-step RT-ddPCR method simplifies the workflow, allows for duplexing reactions, and enables absolute quantification of transcripts without standard materials. With a gene augmentation vector, we demonstrate the application of RT-ddPCR in quantifying vector expression in vitro and in non-human primate (NHP) samples. This novel method is demonstrated to be precise and linear within the range of 0.05–25 ng of RNA input. Using an AAV-RNAi vector, we further demonstrate the utility of this RT-ddPCR method in quantifying potency. Orthogonal potency assays, including ELISA and functional readout, correlate well with RT-ddPCR results. Therefore, one-step RT-ddPCR can be implemented in the analytical and pharmacological characterization of AAV vectors.

Introduction: Hepatocellular carcinoma (HCC) is a common clinical malignancy. Recent studies reported that E2F transcription factor 2 (E2F2) plays a significant role in tumor progression. However, its expression and biological function in HCC are still unclear. Therefore, we explored the relationship between E2F2 expression and tumor progression in HCC. Methods: In this study, we utilized some online tools to explore the E2F2 expression in pan-carcinoma and HCC. The association of E2F2 expression with the clinical characteristics and prognosis of HCC was further studied. In addition, we explored the co-expressed genes of E2F2 and mined the positively/negatively corrected significant genes and excavated the possible functions. Meanwhile, the hub gene set was constructed based on protein–protein interaction (PPI) network, and the relationship between E2F2 and immunity was discovered. Results: We observed that the expression level of E2F2 was generally upregulated in HCC. However, E2F2 expression was not significantly different between HCC and normal tissues in regard to the disease stage 4. Furthermore, we also observed the poor prognosis in patients with high E2F2 expression. The co-expressed genes of E2F2 were identified and further detected. Thereafter, we identified the positively/negatively corrected significant genes and constructed the hub gene network of E2F2 based on PPI network. We also found that E2F2 expression was positively correlated with the infiltration levels of CD4+ T, CD8+ T cells, macrophages, neutrophils, and dendritic cells. Conclusion: Our findings suggested that E2F2 could be a potential prognostic factor for HCC, which could provide a therapeutic target for the molecular treatment of HCC.

Long non-coding RNAs (lncRNAs) are a class of functional RNA molecules that do not encode proteins and are composed of more than 200 nucleotides. LncRNAs play important roles in epigenetic and gene expression regulation. The oncogenic lncRNA GACAT3 was recently discovered to be dysregulated in many tumors. Aberrant expression of GACAT3 contributes to clinical characteristics and regulates multiple oncogenic processes. The association of GACAT3 with a variety of tumors makes it a promising biomarker for diagnosis, prognosis, and targeted therapy. In this review, we integrate the current understanding of the pathological features, biological functions, and molecular mechanisms of GACAT3 in cancer. Additionally, we provide insight into the utility of GACAT3 as an effective diagnostic and prognostic marker for specific tumors, which offers novel opportunities for targeted therapeutic intervention.